class_docstr: Model architecture from:
  https://medium.com/coinmonks/create-a-neural-network-in
      -pytorch-and-make-your-life-simpler-ec5367895199
class_docstr_tok: ["Model","architecture","from",":","https",":","\/\/medium.com\/coinmonks\/create-a-neural-network-in","-pytorch-and-make-your-life-simpler-ec5367895199"]
code: def __init__(self, num_in, num_hidden, num_out) -> None:
      super().__init__()
      self.num_in = num_in
      self.num_hidden = num_hidden
      self.num_out = num_out
      self.lin1 = nn.Linear(num_in, num_hidden)
      self.lin2 = nn.Linear(num_hidden, num_out)
      self.relu1 = nn.ReLU()
      self.sigmoid = nn.Sigmoid()
  
file_path: captum/tests/helpers/classification_models.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new SigmoidModel object from inherited base classes: nn with example: obj = SigmoidModel(num_in, num_hidden, num_out)